Every AI answer is paid for in tokens.
DailyTech.ai explains AI news, models and tools with the numbers that decide them: tokens, context, price and speed.
An estimate for English text: real tokenizers differ by model, often by 10 to 20 percent. A page here means about 500 words.
Latest guides
Prices, limits and models explained with the numbers that decide them, each linked to its source.
Mistral Large 4 Opens Its Weights: What Changes
Mistral Large 4 weights are available. See what changed since preview, current API prices, reasoning modes, license terms, and self-hosting choices.
How Many AI API Requests Can Your App Handle?
Calculate your AI API request capacity from request and token limits, identify the bottleneck, and handle temporary 429s and spend caps correctly.
When Batch AI APIs Actually Save Money
Compare six batch AI APIs, their discounts, limits and deadlines, then calculate the real bill when some requests need a retry.
More guides and analysis
What Fine-Tuning Costs Before and After Training
Calculate fine-tuning training fees, ongoing API costs and break-even traffic using published rates and a worked Gemini example.
Anthropic Expands Science Credits Through 20 Partners
Anthropic's October 28 science expansion routes Claude credits through research partners. See who benefits, what is known, and how to apply.
Cursor vs GitHub Copilot: plans, prices and usage compared
Cursor's plans run from free to $200 a month; GitHub Copilot's from free to $39. How each one measures usage, what the multipliers mean, and which fits how you code.
Context windows explained: how much fits in 128K, 256K and 1M tokens
A 128K-token context window holds about 77,000 to 102,000 English words. What a context window is, the windows of current models, and why the answer needs room too.
Prompt caching explained: how it cuts API bills, provider by provider
Prompt caching charges 2% to 25% of the normal input price for repeated prompt text. How it works, what each provider charges, and when cache writes pay off.
How much VRAM do you need to run an LLM locally?
VRAM needed for 8B, 14B, 32B, 70B and 120B models at F16, Q8 and Q4, worked out from each model's official config, plus what memory bandwidth says about speed.
Tools that measure AI
Free, no sign-up. Each tool answers one question you will run into, and shows its formula and its sources.
How many tokens is my prompt?
Token counter
Paste any text or a file and see it split the way a model reads it.
Count my tokensHow long is a 4,000-token answer?
Words to tokens
Convert words, pages or characters into tokens, and back.
ConvertWhat will 10,000 chats a month cost?
API cost calculator
Your workload priced on each model, from the providers' own price pages.
Estimate my billIs a monthly AI plan cheaper than paying per use?
Subscription or API?
Enter how you use AI and see where a plan pays off.
Compare for my usageWill my whole document fit?
Context window checker
Check a document, codebase or chat against each model's window.
Check a documentCan my GPU run this model?
VRAM calculator
Memory needed by model size and quantization, and a speed estimate.
Check my GPUFollow a topic
Pick what you care about and start with the guide that explains it best.
How we check
Numbers come with a source
Prices, context sizes and benchmark scores link to the provider's own page, with the date we read it.
We say what we did not test
When a result comes from someone else's test, we name them. We do not present other people's work as ours.
Corrections stay visible
When a fact changes or we get one wrong, the article says what changed and when.